CURRENT RESEARCH

 

Precision Planning Inventory Tools for Forest Value Enhancement

(GEOIDE Strategic Investment Initiative) [PI: Treitz]

Forest inventory and management requirements are changing rapidly as forest industries try to satisfy an increasingly complex set of rules, standards, business practices, and public expectations (i.e., economic, environmental and social policy goals). A significant barrier to the sustainable management of forests under these new pressures is a lack of information regarding supply, as forest resources inventories to date have been limited to quantifying merchantable timber. To satisfy these expectations, there is a critical need to develop accurate inventory systems that spatially quantify forest structure and related attributes to enable product segregation and resource value maximization. New remote-sensing and data-processing technologies can provide a very detailed three-dimensional model of the forest, essential for forest resource inventory (FRI) interpretation and ecosite classification. The research proposed here will develop and validate an operational forest inventory system that supports value chain optimization by providing more accurate, precise, and relevant inventory information that may be used to characterize fibre attributes, quality and economic value.

 

Modelling High Arctic permafrost landscape stability and water quality for changing climate and resource development (NSERC Strategic Grant) [PI: Lafrenière, Co-I: Lamoureux and Treitz]

This research project will generate a comprehensive framework for assessing the landscape controls over permafrost disturbance and the impact of disturbances on vegetation and water quality. This integrated research is necessitated by the presence of two large natural gas fields adjacent to the Sabine Peninsula on northern Melville Island, Nunavut. Development of these resources will require unprecedented infrastructure to recover gas and deliver it to a liquefaction plant on the south coast of Melville Island for shipping to southern markets. Prior to industrial development in this High Arctic landscape, a framework to understand and predict the sensitivity of land and water to permafrost disturbances and to regional climate changes is required. The need for this research has been further highlighted by extensive permafrost slope disturbances reported on southern Melville Island in 2007-8, and the impact these localized disturbances have had on land, vegetation, and downstream water quality. This initial work demonstrates the need for integrated landscape research across the different physiographic and bioclimatic gradients that exist where energy resource development will occur. The absence of systematic land/water systems research in the region is acute, but necessary to establish policies that will ensure the appropriate development of the national-scale energy resources on Melville Island. The research team combines the expertise of researchers from Queen's University and the Canada Centre for Remote Sensing to establish a network of study sites that characterize the range of physiographic and bioclimatic conditions in the vicinity of the known gas fields. The research will generate crucial baseline data, cost-effective and innovative strategies for mapping permafrost disturbance and vegetation cover, and a hydrological modeling framework to evaluate the sensitivity of water quality to disturbances. The research team will contribute an integrated understanding of High Arctic systems, train highly qualified personnel, and provide a comprehensive knowledge base to undertake important resource development.

 

 

Evaluation and Development of Lidar Data Acquisition Standards for Forest Inventory Applications and Predictive Forest Ecosite Classification (Ontario Centres of Excellence for Earth and Environmental Technologies – OCEEET) [PI: Treitz]
The goal of this project is to develop standards for collecting, processing and analysing lidar data to derive forest inventory attributes that lead to the production of an enhanced forest resource inventory (eFRI) and associated predictive ecosite classification for Ontario forests. Similar to our ongoing research in the application and testing of lidar for forestry, this research aims to address enhanced forest resource inventory specifically, and the standards around its production and management. There is a strong need to make commercial lidar data operational within a clearly established set of standards for forest inventory derivation and ecosite classification. A software module that incorporates these standards and allows quality analysis of lidar data to generate accurate and repeatable estimates of typical forest inventory attributes and forest ecosite classification, ultimately incorporated within a comprehensive forest inventory management system is the project’s desired outcome.

 

Spectral Analysis of Vegetation Communities for Estimating Biophysical Variables of Northern Ecosystems (NSERC Equipment Grant) [PI: Treitz]
Spectral indices, specifically the normalized difference vegetation index (NDVI) and related indices have been used to characterize biophysical variables and productivity across a range of vegetated ecosystems, including arctic vegetation communities. However, spectral indices are affected by moisture regime, an environmental variable that is closely linked to vegetation community type and productivity. In addition, vegetation is variable with respect to chlorophyll expression, meaning that individual plants express green biomass as well as senesced components as part of their phenological cycle. Hence research will continue on the development of spectral indices and models that better characterize or model community type, above-ground biomass, productivity and carbon flux for heterogeneous arctic ecosystems (i.e., vegetated versus non-vegetated, non-green vegetation, varied glacial tills and substrates) across different moisture regimes. The ASD spectroradiometer allows for spectral signature analysis and indices development for vegetation communities of northern environments. The primary goal of this research is to study spectral reflectance features related to biophysical variable estimation and related processes (i.e., fraction of absorbed photosynthetically active radiation [fPAR], carbon flux, NPP) across an arctic latitudinal gradient in order to determine the sensitivity of remote sensing data to gradual changes in variable properties (e.g., biomass), as in response to increased temperatures/growing degree days and altered moisture regimes that are associated with a warming climate and modified active layer (i.e., depth to permafrost).

 

Modelling Forest Ecosystem Structure using Light Detection and Ranging (Lidar) (Premier’s Research Excellence Award) [PI: Treitz]
Lidar remote sensing captures three-dimensional information on forest structure and provides significant potential for volume and biomass estimation using forest allometry. Interpolation of lidar height data, as well as segmentation of the intensity response are being examined to determine how three-dimensional surfaces of the forest canopy and terrain can be created and utilized to predict the structural nature of the forest. Specific objectives are: (i) to develop and evaluate processing methods for estimating/predicting tree height, leaf area index (LAI), percent cover, biomass, volume, and understory profiles across a range of forest ecosystem types; and (ii) to determine the effect of sampling density on the prediction of structural and biophysical parameters (i.e., identify optimal footprint and sample density against plot level estimates of volume and biomass).

 

Optimizing Ontario-based Wood Pellet Production for Co-firing and Market Development and Penetration Atikokan Bioenergy Research Centre (Ontario Centre of Excellence for Energy – OCEE) [PI: Pollard; Co-I: Treitz and others]

Research into the application of satellite and airborne optical data for the estimation of forest biomass across a range of pure and mixedwood forest stands will be conducted as a component of this larger bioenergy project. These will provide contemporary estimates of a range of forest mensurational parameters, including biomass for a cross-section of forest stand types. Accurate and precise estimates of biophysical variables such as leaf area index (LAI) and biomass, derived from SPOT satellite data, will serve as inputs to calibrate and validate forest productivity models. These, in conjunction with other spatial data for the Atikokan region, will provide information on the sustainability of forest management practices for biofuel production

 

Climate Change and Permafrost Impacts on High Arctic Watershed Fluxes: Cape Bounty, Melville Island Experimental Watershed Observatory (Government of Canada Program for International Polar Year IPY) [PI: Lamoureux, Co-I: Treitz and others]
Research at the Cape Bounty Arctic Watershed Observatory (CBAWO), Melville Island, Nunavut (74º54’ N, 109º35’ W) will investigate how climate change will affect High Arctic rivers, soils and vegetation to provide an unprecedented understanding of the hydrological and ecosystem processes that are sensitive to climate change, and also to predict and anticipate future effects. During the IPY years we are intensively examining how different snowpack and soil temperature conditions affect the spring melt, the amount of sediment and soil erosion, the growth of plants, and the release of dissolved nutrients and greenhouse gases. We will further link our field observations with satellite remote sensing of soil moisture and vegetation cover.

 

Remote Sensing of Environmental Change across Northern Terrestrial Ecosystems
(NSERC Discovery Grant) [PI: Treitz]: See Introduction for overview.

 

 

PAST PROJECTS

 

Hyperspectral Assessment of Acer saccharum Stand Structure

The ability of high spatial resolution CASI hyperspectral data to relate ground-based biophysical variables to reflectance would provide valuable information for the evaluation of structural change to the forest canopy of sugar maple stands. The goal of this work was to identify quantifiable relationships between the spatial distribution of hyperspectral response measured at airborne scales and ground-based biophysical variables measured at the stand level.

Monitoring Land Cover Change Within a Topographically Complex Tropical Watershed Using SPOT Satellite and Structure-Based in situ Data

The primary objective of this study was to investigate the utility of multi-temporal SPOT data for deriving from-to land cover change information for a highly disturbed tropical landscape. It is expected that the increased spatial resolution of SPOT data will be useful for discriminating abrupt land cover boundaries within the study area and that the lower spectral range relative to TM data will still prove useful for discriminating change among the numerous structurally distinct vegetation types present within the watershed.

The Bioindicators Project

The Bioindicators project sought to develop a Forest Condition Rating (FCR) system for stands in Ontario. Initiated in 1996/97 in response to a need for measurable indicators of forest condition, the project focused upon using physiologically based approaches of assessment.

Detection and Mapping of Purple Loosestrife in Wetlands of South-Eastern Ontario Using CASI and IKONOS Remote Sensing Data

The principal objective of this project was to explore the use of high-resolution multispectral imagery for detection, mapping and monitoring of purple loosestrife. Purple loosestrife (Lythrum salicaria) was introduced to the northeastern U.S. and Canada in the 1800s, for ornamental and medicinal uses. Now known as the "purple plague", this invasive plant is a serious threat to wetlands throughout all of Canada and 48 of 50 states in the United States.